Figure 2 - Mordecai equation plot

Figure 6 - Tx wrt time of day (land cover type)

Figure 7 - maps for each time of day

Air Temperature

Biting rates

transmission rates

Figure 7.5 - maps of errors

Biting rates errors

## NULL

transmission rates errors

Figure 8 - statistical illustration showing breakdown by land cover

#, echo=FALSE, warning=FALSE, include = FALSE
all_pixels <- readRDS(here::here("risk_maps",
                               "data", 
                               "processed_data", 
                               "all_pixels.RData"))

ag_types <- c("Vegetable", "Fruit Tree", "Fruit", "Fodder", "Uncultivated", "Nuts")

filter(all_pixels, landcover %in% "Urban") %>% 
  ggplot(aes(x = transmission_prob, fill= time_of_day, alpha = 0.2)) + 
  geom_density()

filter(all_pixels, landcover %in% "Urban") %>% 
  ggplot(aes(x = air_temperature, fill= time_of_day, alpha = 0.2)) + 
  geom_density()

filter(all_pixels, landcover %in% ag_types) %>% 
  ggplot(aes(x = transmission_prob, fill= time_of_day, alpha = 0.2)) + 
  geom_density()

filter(all_pixels, landcover %in% ag_types) %>% 
  ggplot(aes(x = transmission_prob, fill= time_of_day, alpha = 0.2)) + 
  geom_density()

filter(all_pixels, time_of_day == "Day", landcover %in% ag_types) %>%
  ggplot(aes(x = transmission_prob, fill= landcover, alpha = 0.2)) + 
  geom_density()

filter(all_pixels, time_of_day == "Day", landcover %in% ag_types) %>%
  ggplot(aes(x = biting_rate, fill= landcover, alpha = 0.2)) + 
  geom_density()
## Warning: Removed 383617 rows containing non-finite values (stat_density).

filter(all_pixels, time_of_day == "Day", landcover %in% ag_types) %>%
  ggplot(aes(x = air_temperature, fill= landcover, alpha = 0.2)) + 
  geom_density()